Design Curve Construction Based on Two-Stress Level Test Data

2012 ◽  
Author(s):  
Zhigang Wei ◽  
Limin Luo ◽  
Shengbin Lin ◽  
Dmitri Konson ◽  
Fulun Yang
Keyword(s):  
Test Data ◽  
Stress Level ◽  
Design Curve

scholarly journals Perbedaan Stres Persiapan Hari Raya Galungan pada Ibu Rumah Tangga dan Ibu Bekerja yang Beragama Hindu di Denpasar

2013 ◽  
Vol 1 (1) ◽  
Author(s):  
Bagus Galih Hantosa ◽  
Luh Made Karisma Sukmayanti Suarya
Keyword(s):  
Data Analysis ◽  
Test Data ◽  
Stress Level ◽  
Working Mothers ◽  
Sampling Technique ◽  
T Test ◽  
Stress Difference ◽  
Easy Task ◽  
The Difference ◽  
The One

Galungan is Hindu religious holy day in celebrating the triumph of dharma over adharma. In Galungan preparation, the mothers, housewives and working mothers, are the one who in charge to prepare all banten that needed on Galungan. Preparing Galungan’s banten was not an easy task because skill, knowledge and time are needed to prepare all the banten, that why this activity had potential to make stress among housewives and working mothers. This study aimed to discover the difference Galungan preparation’s stress between Hindus housewives and working mothers in Denpasar   Sampling technique used in this research was simple random samplings that were 100 subjects consisting of 52 working and mothers and 48 housewives that lived in Denpasar area, that filled the scale of Galungan Preparation’s Stress that was made by stress aspect from pyshic, emotional, and concentration by Dr. Robert J. an Amberg, Cary Cooper, Alison Straw and Braham. From available 60 items, 55 items was declared dan 5 items fall with reliability value 0,974,. Method of analyzing data used in this research is the analysis of parametric t-test independet group. Results from test data analysis is that there is a significant value of p= 0.000 which indicates a significant stress difference between both group of Hindus housewives and working mothers, which was working mothers have more stress level than housewives when working on Galungan’s preparation.   Keywords : Galungan, Stress, Working Mothers, Housewives

Design Curve Construction Based on Monte Carlo Simulation

2013 ◽  
Author(s):  
Zhigang Wei ◽  
Limin Luo ◽  
Burt Lin ◽  
Dmitri Konson ◽  
Kamran Nikbin
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Sample Size ◽  
Test Data ◽  
Confidence Level ◽  
Small Sample Size ◽  
Test Sample ◽  
Small Sample ◽  
Tolerance Limit ◽  
Design Curve

Good durability/reliability performance of products can be achieved by properly constructing and implementing design curves, which are usually obtained by analyzing test data, such as fatigue S-N data. A good design curve construction approach should consider sample size, failure probability and confidence level, and these features are especially critical when test sample size is small. The authors have developed a design S-N curve construction method based on the tolerance limit concept. However, recent studies have shown that the analytical solutions based on the tolerance limit approach may not be accurate for very small sample size because of the assumptions and approximations introduced to the analytical approach. In this paper a Monte Carlo simulation approach is used to construct design curves for test data with an assumed underlining normal (or lognormal) distribution. The difference of factor K, which measures the confidence level of the test data, between the analytical solution and the Monte Carlo simulation solutions is compared. Finally, the design curves constructed based on these methods are demonstrated and compared using fatigue S-N data with small sample size.

A Bayesian Statistics Based Design Curve Construction Method for Test Data With Extremely Small Sample Sizes

2015 ◽  
Author(s):  
Zhigang Wei ◽  
Limin Luo ◽  
Fulun Yang ◽  
Robert Rebandt
Keyword(s):  
Standard Deviation ◽  
Bayesian Statistics ◽  
Test Data ◽  
Small Sample ◽  
Stress Recovery ◽  
Testing Time ◽  
Design Curve ◽  
Construction Methods ◽  
Recovery Technique ◽  
The Mean

Fatigue design curve construction is commonly used for durability and reliability assessment of engineering components subjected to cyclic loading. A wide variety of design curve construction methods have been developed over the last decades. Some of the methods have been adopted by engineering codes and widely used in industry. However, the traditional design curve construction methods usually require significant amounts of test data in order for the constructed design curves to be consistently and reliably used in product design and validation. In order to reduce the test sample size and associated testing time and cost, several Bayesian statistics based design curve construction methods have been recently successfully developed by several research groups. Among all of these methods, an efficient Monte Carlo simulation based resampling method developed by the authors of this paper is of particular importance. The method is based on a large amount of reliable historical fatigue test data, the associated probabilistic distributions of the mean and standard deviation of the failure cycles, and an advanced acceptance-rejection resampling algorithm. However, finite element analysis (FEA) methods and a special stress recovery technique are required to process the test data, which is usually a time-consuming process. A more straightforward approach that does not require these intermediate processes is strongly preferred. This study presents such an approach, in which the only historical information needed is the distribution of the standard deviation of the cycles to failure. The distribution of the mean is directly calculated from the current tested data and the Central Limit Theorem. Neither FEA nor stress recovery technique is required for this approach, and the effort put into design curve construction can be significantly reduced. This method can be used to complement the previously developed Bayesian methods.

On Fatigue Design Curves for 2.25Cr-1Mo-V Steel Reactors at Elevated Temperature in Code Case 2605

2018 ◽  
Vol 140 (2) ◽  
Author(s):  
Jian-Guo Gong ◽  
Fang Liu ◽  
Fu-Zhen Xuan
Keyword(s):  
Stress Level ◽  
Design Method ◽  
Creep Damage ◽  
Damage Parameter ◽  
Damage Factor ◽  
Cycle Number ◽  
Design Curve ◽  
Fatigue Design ◽  
A Value ◽  
Cyclic Frequency

Fatigue design method for 2.25Cr-1Mo-V steel reactors in code case 2605 (CC 2605) is reviewed. Main factors such as the accelerating function of fatigue action, the cyclic frequency, the strain damage factor (β) related to the fatigue design curves are addressed, and the applicable stress level for pure creep rupture analysis in CC 2605 is also discussed. Results indicate that, for the high loading levels, the accelerating function of fatigue action and strain damage factor contribute relatively remarkably to the fatigue design curve. The increase of cyclic frequency leads to a remarkable increase of the allowable fatigue cycle number and hence reduces the conservativeness of fatigue design curve. It should be stipulated in CC 2605 that the applicable stress level is higher than a value of around 200 MPa (slightly dependent on temperature) for the adjusted uniaxial Omega damage parameter and 16 MPa for the creep strain rate when the Omega creep-damage method is employed.

PROBABILISTIC SPECIMEN PROPERTY-FATIGUE LIFE MAPPING AND P-S-N CURVE FITTING

2013 ◽  
Vol 20 (05) ◽  
pp. 1350020
Author(s):  
LIYANG XIE ◽  
JIANZHONG LIU ◽  
NINGXIANG WU ◽  
WENXUE QIAN
Keyword(s):  
Fatigue Life ◽  
Test Data ◽  
Stress Level ◽  
Curve Fitting ◽  
Cyclic Stress ◽  
Small Sample ◽  
Test Method ◽  
Life Distribution ◽  
Stress Levels ◽  
Curve Fitting Method

Fitting P-S-N curve with small-size sample of fatigue test data is significant in engineering applications. Although several small sample-based P-S-N curve fitting methods have been developed, complexity in mathematics and/or the unrealistic assumption of the methods hinder their application seriously. Based on the principle of probabilistically mapping from the probability distribution of specimen property to that of fatigue life of the specimen, this paper presents a new, easy to apply P-S-N curve fitting method. By collecting the life distribution information dispersed in several small-size samples of fatigue lives tested under different cyclic stress levels, a large-size sample of equivalent fatigue life data can be built based on the mapping mechanism as well as the uniqueness of the relationship between fatigue life standard deviation and cyclic stress level. The basic viewpoint is that the fatigue lives tested at any cyclic stress levels can be equivalently converted to an arbitrary baseline stress level according to the life distribution–stress relationship, and this principle can be applied to determine the P-S-N curves with a limited number of test data. Test results illustrate that the P-S-N curves obtained by such methods with 30, 24 or 20 samples, respectively, are close to those obtained by the conventional test method with 60 or 40 samples.

A Probabilistic Fatigue Damage Model for Describing the Entire Set of Fatigue Test Data of the Same Material

2019 ◽  
Author(s):  
Xiaobin Le
Keyword(s):  
Fatigue Test ◽  
Fatigue Damage ◽  
Test Data ◽  
Stress Level ◽  
Damage Model ◽  
Fatigue Tests ◽  
Small Sample ◽  
Test Machine ◽  
Stress Levels ◽  
D Model

Abstract One typical widely-accepted approach for describing the fatigue test data is the P-S-N curve approach. However, the P-S-N curve approach has some issues such as: (1) If there are only a few fatigue test data at a fatigue test stress level, the P-S-N curve approach is not valid due to the small sample size; (2) When the total number of fatigue tests under different stress levels might be larger such as more than 30 even though the number of fatigue tests at the same stress level is small, the P-S-N curve cannot be used to analyze such set of fatigue data; (3) It is difficult to calculate the reliability of a component under a cyclic stress level when the probabilistic distribution function under this stress level is not available in the P-S-N curves. The author has proposed the K-D probabilistic fatigue damage model (K-D model) to overcome those issues. The 6061-T6 10-gauge sheet-type flat fatigue specimen was designed, manufactured, and tested on the Instron 8081 fatigue test machine to verify this K-D model. The fatigue tests were under five different cyclic axial loadings with a total of 195 tests. In this paper, the fatigue test data will be analyzed by the P-S-N curve approach and the K-D model. The systematic comparisons between the P-S-N curve approach and the K-D model have approved and verified that the K-D model can be used to analyze and to describe the fatigue test data under all different fatigue stress levels and can be used to calculate the reliability of a component under any type of cyclic fatigue loading.

Estimation of Creep Deformation in Components From Short-Term Proof Test Data

1983 ◽  
Vol 105 (2) ◽  
pp. 179-184
Author(s):  
D. L. Marriott
Keyword(s):  
Experimental Data ◽  
Test Data ◽  
Stress Level ◽  
Creep Deformation ◽  
Short Term ◽  
Design Procedures ◽  
General Stress ◽  
Reference Stress

The paper describes a technique for estimating creep deformation from the results of short-term proof tests. The method relies on the concept of a reference stress which is representative of the general stress level in the component. It is shown that the method provides an upper, and therefore safe, bound on creep deformation. Application to a complex piping component is used to illustrate the procedure and some of the practical problems of interpreting the experimental data. Finally, an attempt is made to relate the reference stress method to tentative design procedures in Code Case N.47 of the ASME III Code.

Test Validation Without Measurement

2016 ◽  
Vol 32 (3) ◽  
pp. 204-214 ◽  
Author(s):  
Emilie Lacot ◽  
Mohammad H. Afzali ◽  
Stéphane Vautier
Keyword(s):  
Test Data ◽  
Test Scores ◽  
Scientific Explanation ◽  
Test Validation ◽  
Clinical Tests ◽  
Ethical Perspective ◽  
Power Of Test ◽  
Memory Accuracy ◽  
Social Uses ◽  
Special Case

Abstract. Test validation based on usual statistical analyses is paradoxical, as, from a falsificationist perspective, they do not test that test data are ordinal measurements, and, from the ethical perspective, they do not justify the use of test scores. This paper (i) proposes some basic definitions, where measurement is a special case of scientific explanation; starting from the examples of memory accuracy and suicidality as scored by two widely used clinical tests/questionnaires. Moreover, it shows (ii) how to elicit the logic of the observable test events underlying the test scores, and (iii) how the measurability of the target theoretical quantities – memory accuracy and suicidality – can and should be tested at the respondent scale as opposed to the scale of aggregates of respondents. (iv) Criterion-related validity is revisited to stress that invoking the explanative power of test data should draw attention on counterexamples instead of statistical summarization. (v) Finally, it is argued that the justification of the use of test scores in specific settings should be part of the test validation task, because, as tests specialists, psychologists are responsible for proposing their tests for social uses.

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